Binocular measurement device, binocular measurement method, and binocular measurement program

ABSTRACT

An object is to simply and easily evaluate differences in behavior of the eyes of subjects. A binocular measurement system  1  includes a photodetector  7  that detects reflected light from the right eye E R  and the left eye E L  of a subject, and outputs image signal of the reflected light, a feature amount calculating unit  11  that calculates a feature amount corresponding to the right eye E R  and a feature amount corresponding to the left eye E L  based on the image signal, and a comparison value calculating unit  13  that calculates, based on the two feature amounts, a comparison value obtained by comparing the two feature amounts.

TECHNICAL FIELD

An aspect of the present invention relates to a binocular measurementdevice, a binocular measurement method, and a binocular measurementprogram to measure both eyes of a target person.

BACKGROUND ART

The eye is an organ differentiated from the brain in an organic process,and is only one organ capable of being observed non-invasively from theoutside among organs directly linked to the brain. Therefore, it isconsidered that the health of the brain can be quantified by quantifyingbehavior of the eye area. Conventionally, for quantitative evaluation ofbrain functions, large-scale facilities such as PET (positron emissiontomography), CT, and MRI are used. Such quantitative evaluation hasachieved a measure of credibility. On the other hand, such quantitativeevaluation has a problem in which the cost burden is high, and a doctorwith specialized expertise for diagnosis is necessary. Therefore, it hasbeen demanded to establish evaluation by a more convenient method.

On the other hand, conventionally, as one method of brain functionmeasurement methods, a method for inspecting behavior of the eyes of asubject has been known. For example, a method for measuring eye blinkingof a subject (refer to Non Patent Literature 1 listed below), and amethod for measuring involuntary eye movement of a subject (refer to NonPatent Literature 2 listed below), etc., have been considered as one ofthe convenient methods for brain function disease extraction andscreening.

CITATION LIST Non Patent Literature

-   Non Patent Literature 1: Takahiro Niida, “Neuro-ophthalmology    Introduction Series 96, Palpebra 2, Blinking,” Neuro-ophthalmol.    Jpn. Vol. 29 No. 2, pp. 204-212, 2012-   Non Patent Literature 2: Engbert R., “Microsaccades: amicrocosm for    research on oculomotor control, attention, and visual perception,”    Martinez-Conde, Macknik, Martinez, Alonso & Tse (Eds.), Progress in    Brain Research, 2006, vol. 154, pp. 177-192

SUMMARY OF INVENTION Technical Problem

However, with the method described in Non Patent Literature 1 listedabove, a reflexive eyeblink caused by electrostimulation is measured byusing an evoked potential recording device with a plurality ofelectrodes, and a burden on a subject at the time of an inspection tendsto increase. In addition, by the methods described in Non PatentLiterature 1 and Non Patent Literature 2, it is difficult to properlyevaluate differences in behavior of both eyes of subjects.

Therefore, an aspect of the present invention was made in view of theseproblems, and an object thereof is to provide a binocular measurementdevice and a binocular measurement method capable of easily and properlyevaluating differences in behavior of both eyes of subjects.

Solution to Problem

In order to solve the above-described problems, the inventors of thepresent invention examined a method of quantitative evaluation ofdifferences in behavior of both eyes between patients suffering fromvarious diseases such as Parkinson's disease and healthy people. As aresult, the inventors of the present invention found that evaluation ofa comparison value obtained by comparing a feature amount calculatedbased on movement of the right eye and a feature amount calculated basedon movement of the left eye could be used as a new index fordiscrimination between a brain disease patient and a healthy person orfor quantitative evaluation of states before and after a fatigue work.

That is, a binocular measurement device according to an embodiment ofthe present invention includes a photodetector that detects light fromthe right eye and the left eye of a target person, and outputs detectionsignal of the light, a feature amount calculating unit that calculates afirst feature amount corresponding to the right eye and a second featureamount corresponding to the left eye based on the detection signal, anda comparison value calculating unit that calculates, based on the firstfeature amount and the second feature amount, a comparison valueobtained by comparing the first feature amount and the second featureamount.

Alternatively, a binocular measurement method according to anotherembodiment of the present invention includes a step of detecting lightfrom the right eye and the left eye of a target person by using aphotodetector, and outputting a detection signal of the light, a step ofcalculating a first feature amount corresponding to the right eye and asecond feature amount corresponding to the left eye based on thedetection signal, and a step of calculating, based on the first featureamount and the second feature amount, a comparison value obtained bycomparing the first feature amount and the second feature amount.

Alternatively, a binocular measurement program according to anotherembodiment of the present invention makes a processor included in abinocular measurement device that measures both eyes of a target personby using an image of a portion including the right eye and the left eyeof the target person, function as a feature amount calculating unit thatcalculates a first feature amount corresponding to the right eye and asecond feature amount corresponding to the left eye based on the image,and a comparison value calculating unit that calculates, based on thefirst feature amount and the second feature amount, a comparison valueobtained by comparing the first feature amount and the second featureamount.

By the binocular measurement device, the binocular measurement method,or the binocular measurement program according to the embodimentsdescribed above, based on detection signal (image) of light from theright eye and the left eye, a first feature amount related to the righteye and a second feature amount related to the left eye are calculated,and a comparison value obtained by comparing the first feature amountand the second feature amount is calculated. Accordingly, an evaluationvalue related to behavior of the eyes of the target person can beacquired with a simple device configuration without a burden on thetarget person. Further, based on this evaluation value, behavior of theeyes of the target person can be properly evaluated.

Advantageous Effects of Invention

According to an aspect of the present invention, differences in behaviorof both eyes of subjects can be easily and properly evaluated.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram showing a schematic configuration of abinocular measurement system 1 according to an embodiment of the presentinvention.

FIG. 2 are graphs showing temporal changes of an upper eyelid positionand an upper eyelid movement speed calculated by a feature amountcalculating unit 11 shown in FIG. 1.

FIG. 3 is a flowchart showing steps of a comparison value measurementoperation by the binocular measurement system 1 shown in FIG. 1.

FIG. 4 is a flowchart showing steps of a comparison value measurementoperation by the binocular measurement system 1 shown in FIG. 1.

FIG. 5 are graphs showing frequency values of right-left differences intime of maximum speed of eye closing in eye blinking and frequencyvalues of right-left differences in maximum speed of eye closing in eyeblinking obtained by the binocular measurement system 1 shown in FIG. 1.

FIG. 6 are graphs showing mean values of right-left differences in timeof maximum speed of eye closing in eye blinking and variance values ofright-left differences in time of maximum speed of eye closing in eyeblinking.

FIG. 7 are graphs showing standard deviations of right-left differencesin time of maximum speed of eye closing in eye blinking and differencesbetween maximum values and minimum values of right-left differences intime of maximum speed of eye closing in eye blinking obtained by thebinocular measurement system 1 shown in FIG. 1.

FIG. 8 are graphs showing maximum values of right-left differences intime of maximum speed of eye closing in eye blinking and minimum valuesof right-left differences in time of maximum speed of eye closing in eyeblinking obtained by the binocular measurement system 1 shown in FIG. 1.

FIG. 9 are graphs showing mean values of right-left differences inmaximum speed of eye closing in eye blinking and variance values ofright-left differences in maximum speed of eye closing in eye blinkingobtained by the binocular measurement system 1 shown in FIG. 1.

FIG. 10 are graphs showing standard deviations of right-left differencesin maximum speed of eye closing in eye blinking and differences betweenmaximum values and minimum values of right-left differences in maximumspeed of eye closing in eye blinking obtained by the binocularmeasurement system 1 shown in FIG. 1.

FIG. 11 are graphs showing maximum values of right-left differences inmaximum speed of eye closing in eye blinking and minimum values ofright-left differences in maximum speed of eye closing in eye blinkingobtained by the binocular measurement system 1 shown in FIG. 1.

FIG. 12 are graphs showing a distribution of mean values of maximumspeeds of eye closing in eye blinking of the left eyes, a distributionof mean values of maximum speeds of eye closing in eye blinking of theright eyes, and a distribution of right-left differences in mean valueof maximum speeds of eye closing in eye blinking obtained by thebinocular measurement system 1 shown in FIG. 1.

FIG. 13 are graphs showing mean values and standard deviations ofright-left differences in time of maximum speed of eye closing in eyeblinking, and mean values and standard deviations of right-leftdifferences in maximum speed of eye closing in eye blinking obtained bythe binocular measurement system 1 shown in FIG. 1.

FIG. 14 are graphs showing frequencies of right-left differences in meanvalue of upper eyelid movement amounts at the time of eye closing in eyeblinking, frequencies of right-left differences in mean value of periodsof eye closing in eye blinking, and frequencies of right-leftdifferences in mean value of eye closure periods obtained by thebinocular measurement system 1 shown in FIG. 1.

FIG. 15 are graphs showing frequencies of right-left differences in meanvalue of upper eyelid movement amounts at the time of eye opening in eyeblinking, frequencies of right-left differences in mean value of periodsof eye opening in eye blinking, and frequencies of right-leftdifferences in mean value of maximum speeds of eye opening in eyeblinking obtained by the binocular measurement system 1 shown in FIG. 1.

FIG. 16 are graphs showing a temporal change of an eyeball movementspeed and a temporal change of an eyeball position calculated by thefeature amount calculating unit 11 shown in FIG. 1.

FIG. 17 are graphs showing examples of temporal changes of eyeballpositions calculated by the feature amount calculating unit 11 shown inFIG. 1.

FIG. 18 is a flowchart showing steps of a comparison value measurementoperation by the binocular measurement system 1 shown in FIG. 1.

FIG. 19 is a flowchart showing detailed steps of involuntary eyemovement analysis by the binocular measurement system 1 shown in FIG. 1.

FIG. 20 is a flowchart showing detailed steps of involuntary eyemovement analysis by the binocular measurement system 1 shown in FIG. 1.

FIG. 21 is a flowchart showing detailed steps of involuntary eyemovement analysis by the binocular measurement system 1 shown in FIG. 1.

FIG. 22 is a flowchart showing steps of a comparison value measurementoperation by the binocular measurement system 1 shown in FIG. 1.

FIG. 23 are graphs showing right-left differences in flick maximum speedand right-left differences in time of flick maximum speed obtained bythe binocular measurement system 1 shown in FIG. 1.

FIG. 24 are graphs showing frequency values of right-left differences inflick width, frequency values of right-left differences in flickmovement distance, frequency values of right-left differences in flickangle at maximum speed, and frequency values of right-left differencesin angle of flick period.

FIG. 25 are graphs showing mean values of right-left differences inmovement frequency of tremor and standard deviations of the right-leftdifferences obtained by the binocular measurement system 1 shown in FIG.1.

FIG. 26 are graphs showing examples of temporal changes of pupildiameters calculated by the feature amount calculating unit 11 shown inFIG. 1.

FIG. 27 is a flowchart showing steps of a comparison value measurementoperation by the binocular measurement system 1 shown in FIG. 1.

FIG. 28 is a flowchart showing steps of a comparison value measurementoperation by the binocular measurement system 1 shown in FIG. 1.

DESCRIPTION OF EMBODIMENTS

Hereinafter, preferred embodiments of a binocular measurement device, abinocular measurement method, and a binocular measurement programaccording to the present invention will be described in detail withreference to the drawings. In addition, the same or corresponding partswill be denoted by the same reference signs in the description of thedrawings, and overlapping description will be omitted.

FIG. 1 is a block diagram showing a schematic configuration of abinocular measurement system 1 according to a preferred embodiment ofthe present invention. The binocular measurement system 1 shown in FIG.1 is configured to temporally continuously detect light from the righteye E_(R) and the left eye E_(L) of a subject (target person) at apredetermined frame rate, and quantify and output differences inbehavior between the right and left eyes of the subject. This binocularmeasurement system 1 includes light sources 3R and 3L that irradiateillumination light onto the right eye E_(R) and the left eye E_(L) of atarget person, a lighting control device 5 that controls the lightsources 3R and 3L, a photodetector 7 that detects light from the righteye E_(R) and the left eye E_(L), and a processor 9 that processesdetection signal output from the photodetector 7.

The light sources 3R and 3L are illuminating means that illuminates theright eye E_(R) and the left eye E_(L) of a subject including theirperipheries, and preferably consist of, for example, LEDs that generateinfrared light. When the light sources 3R and 3L irradiate infraredlight onto the eyes E_(R) and E_(L) and their peripheries, the infraredlight is reflected on the eyes E_(R) and E_(L) and their peripheries andlight images are generated. The light sources 3R and 3L are not limitedto the infrared LEDs, and other kinds of light sources may be used. Forexample, light sources that generate near infrared light may be used,lamp light sources combined with films that transmit infrared light ornear infrared light may be used, or laser beams satisfying safetystandards may be used as direct light or indirect light. In addition, asa configuration to realize proper illuminance, in addition to aconfiguration using a plurality of illumination lamps, these lightsources may have a configuration in which a lens is incorporated in alight emitting unit to suppress scattering of the illumination light andefficiently illuminate a desired region. In these light sources, aconfiguration that performs efficient eye area illumination by shapingenergy of a laser beam into a desired lighting shape by using a spatialmodulation device, may be adopted.

The lighting control device 5 is a control unit that controls lightintensities of the light sources 3R and 3L so as to respectivelyilluminate the right eye E_(R) and the left eye E_(L) of a subject atpredetermined brightness. In addition, the lighting control device 5adjusts and controls light intensities and emission wavelengths of thelight sources 3R and 3L so as to obtain light intensities, illuminationlight wavelengths, and reflected light shapes suitable for details ofdetection targeting the right eye E_(R) and the left eye E_(L) of asubject. Further, the lighting control device 5 is electricallyconnected to the processor 9, and according to synchronous control bythe processor 9, controls light emission timings with respect to theright eye E_(R) and the left eye E_(L) of a subject. In order to enablethe processor 9 or the photodetector 7 to determine whether the righteye E_(R) and the left eye E_(L) of a subject are within a measurementrange of the photodetector 7, or in order to realize a function ofpositioning the right eye E_(R) and the left eye E_(L) of a subject bythe processor 9 or the photodetector 7, the lighting control device 5may control illumination light of the light sources 3R and 3L to flashbefore the start of measurement.

The photodetector 7 is an imaging device that has a light receivingsurface with a plurality of pixels two-dimensionally arrayed, anddetects reflected light from the right eye E_(R) and the left eye E_(L)at a predetermined frame rate and generates and outputs two-dimensionalimage signal (detection signal). As such an imaging device, a visioncamera having a vision chip that performs processing from imageacquisition to image processing can be used. As this photodetector 7,two photodetectors may individually and respectively capture the righteye E_(R) and the left eye E_(L) of a subject, or one photodetector maysimultaneously capture the right eye E_(R) and the left eye E_(L) of asubject. The photodetector 7 may be combined with a plurality of imagingdevices that have specifications or settings (for example, wavelengthsensitivity, light intensity sensitivity, angle of view of lens,magnification of lens, and frame rate, etc.) respectively optimal foreyeball movement, involuntary eye movement, eye blinking, and pupils tobe detected of a subject.

The photodetector 7 is preferably configured to be capable of performingcapturing at a frame rate higher than that of a general video camera,and is preferably set to have a frame rate of a frequency twice or moreas high as a movement frequency to be detected of a subject. Forexample, when tremor of involuntary eye movement is to be detected,tremor is movement of approximately 100 Hz, so that a photodetector 7with a frame rate of 200 Hz or more is used. When microsaccade is to bedetected, microsaccade takes approximately 20 msec in many cases, sothat a photodetector 7 with a frame rate of 100 Hz or more is used. Aneyelid movement at the time of eye blinking takes approximately 200msec, so that when the frame rate is approximately 10 Hz, rough eyelidmotion behavior can be detected. However, in order to enable detectionof fine irregular movement at the time of eye blinking, not only a highframe rate but also high accuracy are required for the measurement.Therefore, when eyelid movement at the time of eye blinking is to bedetected, a photodetector 7 configured not only to have a high framerate but also to be capable of imaging at high resolution is used.

Here, a photodetector 7 other than a video camera may be used. In a casewhere eyeball movement and involuntary eye movement are to be detectedand a video camera is used as the photodetector 7, cornea reflectedlight is detected from image signals, and by gravity center arithmeticoperation, temporal changes of eyeball positions are obtained. Instead,as the photodetector 7, in addition to a sensor such as a profile sensorthat detects a position of a bright spot and outputs positionalinformation, a simpler sensor such as a photodiode, a photodetector, alinear sensor, or an area sensor may be used. In a case where eyeblinking is to be detected and a video camera is used as thephotodetector 7, eyelid position extraction processing using imageprocessing technologies such as edge extraction and Hough transform, orprocessing to obtain an eyelid position from a luminance profilecalculated from an image signal, is performed. Instead, as thephotodetector 7, a configuration including a lighting unit (for example,a line laser, an LED array, etc.) that irradiates and projects a markerhaving a linear shape or the like on an eye area, and a detection unit(for example, a profile sensor, a photodiode, a photodetector, a linearsensor, an area sensor, etc.) that extracts an eyelid position bycapturing reflection on an eye surface without capturing scattered lighton the skin, may be adopted. In a case where the pupils are to bedetected and a video camera is used as the photodetector 7, byextracting a portion made bright by reflected light generated whenirradiating illumination light onto the pupil from the front side bybinarization of image processing, a pupillary area is extracted.Instead, it is also allowed that information on a temporal change of apupillary area is acquired by detecting a sum of brightness values ofthe portion made bright by using a photodiode or a photodetector. Thesum of brightness values detected herein bears a proportionaterelationship to the pupillary area.

The processor 9 is an image processing circuit, and processes imagesignals output from the photodetector 7. The processor 9 is constitutedby a personal computer with a CPU and a memory such as a RAM or a ROMincorporated inside, or a mobile terminal, etc., typified by asmartphone or a tablet computer. The processor 9 may also be constitutedby an FPGA (field programmable gate array). This processor 9 includes,as functional constituent elements, a feature amount calculating unit11, a comparison value calculating unit 13, a result output unit 15, anda synchronous control unit 17. The feature amount calculating unit 11,comparison value calculating unit 13, result output unit 15, andsynchronous control unit 17 may be realized by hardware inside theprocessor 9, or may be realized by software (a binocular measurementprogram) stored in the processor 9. Functions of the feature amountcalculating unit 11, the comparison value calculating unit 13, theresult output unit 15, and the synchronous control unit 17 may berealized by the same processor, or may be realized by differentprocessors. A program to make the processor 9 function as the featureamount calculating unit 11, the comparison value calculating unit 13,the result output unit 15, and the synchronous control unit 17 may bestored in a storage device (storage medium) inside the processor 9, ormay be stored in a storage medium electrically connected to theprocessor 9.

The feature amount calculating unit 11 of the processor 9 calculates aright eye feature amount corresponding to the right eye E_(R) of asubject and a left eye feature amount corresponding to the left eyeE_(L) of the subject based on image signal output from the photodetector7. For example, as a right eye feature amount and a left eye featureamount, the feature amount calculating unit 11 calculates a featureamount related to eye blinking, a feature amount related to involuntaryeye movement, and a feature amount related to the pupil. At this time,the feature amount calculating unit 11 may calculate all of these threekinds of feature amounts, or may calculate a part of them. Theinvoluntary eye movement to be calculated as a feature amount includestremor being fine movement with an amplitude of approximately 1 μm (20to 40 arcseconds) and a frequency of about 100 Hz, drift being slowdisplacing movement, and flick (also referred to as microsaccade) beingsaccadic eye movement (saltation movement) of 0.04 degree angle to 2minutes of arc occurring after drift.

Based on the right eye feature amount and the left eye feature amountcalculated by the feature amount calculating unit 11, the comparisonvalue calculating unit 13 of the processor 9 calculates a comparisonvalue obtained by comparing a right eye feature amount and a left eyefeature amount. The comparison value calculating unit 13 may directlycalculate a comparison value from the right eye feature amount and theleft eye feature amount, or may calculate statistics from the respectiveright eye feature amount and left eye feature amount, and calculate acomparison value of these statistics. Such statistics are statisticsobtained from high-order moments such as a mean, a variance, a standarddeviation, kurtosis, and skewness, a median value, a quartile point, amaximum value, a minimum value, a mode value, and a difference betweenthe maximum value and the minimum value, etc. At this time, thecomparison value calculating unit 13 calculates, as a comparison value,an absolute value of a difference between the right eye feature amountand the left eye feature amount, or a ratio between the right eyefeature amount and the left eye feature amount.

The result output unit 15 of the processor 9 outputs a comparison valuecalculated by the comparison value calculating unit 13 to an outputdevice such as a display. At this time, the result output unit 15 mayoutput a comparison value to the outside by using wirelesscommunications, wired communications, or the like, or output acomparison value to the memory inside. The result output unit 15 mayoutput, in addition to numerical data represented by a comparison value,text data and acquired images as they are, or may output statistics ofnumerical data showing comparison values. Such statistics are statisticsobtained from high-order moments such as a mean, a variance, a standarddeviation, kurtosis, and skewness, a median value, a quartile point, amaximum value, a minimum value, a mode value, and a difference betweenthe maximum value and the minimum value, etc. The result output unit 15may output an aggregated value such as a mean value obtained byaggregating comparison values, or may set a threshold and output aperiod during which a comparison value exceeds the threshold, or similardata, and frequency, etc.

The synchronous control unit 17 of the processor 9 controlssynchronization of operations of the respective devices and therespective function units in the binocular measurement system 1. Forexample, the synchronous control unit 17 controls synchronizationbetween a timing of capturing (detection) by the photodetector 7 andemission timings of the light sources 3R and 3L. The synchronous controlunit 17 controls operation timings of the feature amount calculatingunit 11, the comparison value calculating unit 13, and the result outputunit 15 according to output timings of image signals by thephotodetector 7. For the processor 9, a configuration that makes therespective devices and the respective function units operateasynchronously by using a shared memory instead of the synchronouscontrol unit 17 may be adopted. For example, the photodetector 7occasionally saves image data based on image signal in a shared memory,and the feature amount calculating unit 11 occasionally monitors whetherimage data has been newly saved in the shared memory, and calculates aright eye feature amount and a left eye feature amount at a timing atwhich saving is detected, and saves these in the shared memory. At thesame time, the comparison value calculating unit 13 occasionallymonitors whether a right eye feature amount and a left eye featureamount have been newly saved in the shared memory, and at a timing atwhich saving of new right eye feature amount and left eye feature amountis detected, calculates a comparison value based on these amounts astargets and saves the comparison value in the shared memory. Similarly,the result output unit 15 always monitors whether a comparison value hasbeen saved in the shared memory, and at a timing at which saving of anew comparison value is detected, outputs the comparison value and datarelated to the comparison value. The result output unit 15 may output acomparison value at a timing at which it receives signals of ends ofprocessing from the photodetector 7, the feature amount calculating unit11, and the comparison value calculating unit 13. In this case, controlof the lighting control device 5 may be performed from the photodetector7, or may be performed from the feature amount calculating unit 11 orthe comparison value calculating unit 13 inside the processor 9.

Here, the lighting control device 5 described above may be incorporatedin the photodetector 7 or the processor 9. For example, when a visioncamera having an arithmetic operation function is used as thephotodetector 7, the photodetector 7 has a function to output processingresults and external control signals, etc., in addition to an imageprocessing function. By using this photodetector 7, real-time controlsuch as flashing control, etc., of the light sources 3R and 3L may beperformed in parallel with image processing.

Similarly, a part or all of the function units of the processor 9 may beincorporated in the photodetector 7. For example, a pattern in which thephotodetector 7 performs processing up to output of image signals andsubsequent processing is performed by the processor 9 may be adopted, apattern in which a part of processing of the feature amount calculatingunit 11 is performed by the photodetector 7 and subsequent processing isperformed by the processor 9 may be adopted, or a pattern in whichprocessing up to feature amount calculation processing of the featureamount calculating unit 11 is performed by the photodetector 7 andsubsequent processing is performed by the processor 9 may be adopted.

The photodetector 7 or the processor 9 may have a function to determinewhether the right eye E_(R) and the left eye E_(L) of a subject arewithin a measurement range of the photodetector 7. In detail, theprocessor 9 performs control to make the light sources 3R and 3L flashwith a predetermined period by the lighting control device 5 before thestart of measurement, and simultaneously, by determining whether aportion that flashes with a predetermined period and at a predeterminedluminance is present in an image signal acquired by the photodetector 7,and deter mines whether an eye area is present within the measurementrange. This utilizes a fact that illumination light scatters on the skinand hair and is reflected on an eye area, and as a result, an eye areais caught brightly in an image signal. By controlling the two lightsources 3R and 3L so as to flash at different periods, the processor 9can grasp the positions of the right eye E_(R) and the left eye E_(L).Since positions of both eyes E_(R) and E_(L) can be grasped, in the casewhere a video camera is used as the photodetector 7, by partiallyreading only a portion corresponding to an eye area in an image signal,it becomes possible to set a frame rate for measurement to be higher,and reduce a file size of a data region to be used to save image data.

Hereinafter, the function of the processor 9 to calculate featureamounts and comparison values will be described in detail. The processor9 of the present embodiment is set to detect eye blinking of a subject.

The feature amount calculating unit 11 of the processor 9 calculates atemporal change of an upper eyelid position based on an image signaloutput from the photodetector 7. The upper eyelid position is calculatedby applying image processing such as edge extraction and Hough transformtargeting the image signal, or processing to obtain an eyelid positionfrom a luminance profile calculated from the image signal (refer toJapanese Unexamined Patent Publication No. 2012-085691). In addition,the feature amount calculating unit 11 calculates a temporal change ofan upper eyelid movement speed based on the temporal change of the uppereyelid position. A portion (a) of FIG. 2 is a graph showing an exampleof a temporal change of an upper eyelid position calculated by thefeature amount calculating unit 11, and a portion (b) of FIG. 2 is agraph showing an example of a temporal change of an upper eyelidmovement speed calculated by the feature amount calculating unit 11.±Vth shown in the portion (b) of FIG. 2 shows an eyeblink motiondetection threshold. A period in which the upper eyelid moves at a speedhigher than this threshold is defined as an eye blinking period, and asshown in the portion (a) of FIG. 2, lowering and rising of the uppereyelid position according to eyeblink motion of the subject aredetected, and as shown in the portion (b) of FIG. 2, a peak of the speedduring lowering of the upper eyelid position and a peak of the speedduring rising of the upper eyelid position are detected. Thus, a statewhere the upper eyelid positioned at the upper side in an eye openingstate lowers according to eye blinking, and when it fully lowers, an eyeclosure state is maintained for a while, and then, the eye is graduallyopened is shown. A state where the upper eyelid movement speed changesto decrease at the time of eye closure, and the upper eyelid movementspeed changes to increase at the time of eye opening, is shown. Thefeature amount calculating unit 11 calculates the temporal change of theupper eyelid position and the temporal change of the upper eyelidmovement speed for each of the right eye E_(R) and the left eye E_(L),separately.

Further, the feature amount calculating unit 11 calculates an eyeblinkfeature amount being a feature amount related to eye blinking for eachof the right eye E_(R) and the left eye E_(L), separately, based on thecalculated temporal change of the upper eyelid position and thecalculated temporal change of the upper eyelid movement speed. First, bycomparing the temporal change of the upper eyelid movement speed with anegative speed threshold −V_(th) set in advance, the feature amountcalculating unit 11 identifies a time the upper eyelid movement speedexceeds the speed threshold −V_(th) from the start of eye blinking as astart time t1 of a period T1 of eye closing in eye blinking, andidentifies a time the upper eyelid movement speed starts to fall belowthe speed threshold −V_(th) again after the time t1 as an ending time t2of the period T1 of eye closing in eye blinking and as a start time t2of an eye closure period T2. Further, the feature amount calculatingunit 11 identifies, in the temporal change of the upper eyelid movementspeed, a time the upper eyelid movement speed starts to surpass thepositive speed threshold +V_(th) set in advance after the time t2 as anending time t3 of the eye closure period T2, and as a start time t3 of aperiod T3 of eye opening in eye blinking, and identifies a time theupper eyelid movement speed starts to fall below the speed threshold+V_(th) again after the time t3 as an ending time t4 of the period T3 ofeye opening in eye blinking. Then, the feature amount calculating unit11 calculates, as an eyeblink feature amount, at least one of a “timeinterval from previous eye blinking,” an “upper eyelid movement amountduring eye closing in eye blinking,” a “period of eye closing in eyeblinking,” a “maximum speed of eye closing in eye blinking,” a “time ofmaximum speed of eye closing in eye blinking,” an “eye closure period,”an “upper eyelid movement amount during eye opening in eye blinking,” a“period of eye opening in eye blinking,” a “maximum speed of eye openingin eye blinking,” and a “time of a maximum speed of eye opening in eyeblinking.” The “time interval from the previous eye blinking” iscalculated as a period T0 between the start time t1 detected at the timeof the previous eyeblink motion and the start time t1 detected at thistime. The “upper eyelid movement amount during eye closing in eyeblinking” is calculated as a movement amount ΔP1 of the upper eyelidduring the period T1 of eye closing in eye blinking, the “period of eyeclosing in eye blinking” is calculated as a length of the period T1, the“maximum speed of eye closing in eye blinking” is calculated as amaximum speed in the period T1, the “time of the maximum speed of eyeclosing in eye blinking” is calculated as a time the speed is detected,and the “eye closure period” is calculated as a length of the period T2.Further, the “upper eyelid movement amount during eye opening in eyeblinking” is calculated as a movement amount ΔP2 of the upper eyelid inthe period T3 of eye opening in eye blinking, the “period of eye openingin eye blinking” is calculated as a length of the period T3, the“maximum speed of eye opening in eye blinking” is calculated as amaximum speed in the period T3, and the “time of maximum speed of eyeopening in eye blinking” is calculated as a time the speed is detected.

The comparison value calculating unit 13 of the processor 9 calculates acomparison value by using the eyeblink feature amounts of the respectiveright eye E_(R) and left eye E_(L) calculated by the feature amountcalculating unit 11. The comparison value calculating unit 13 maydirectly calculate a comparison value from the two eyeblink featureamounts, or may calculate statistics from the two eyeblink featureamounts, and calculate a comparison value of the statistics. In the caseof calculation of statistics, for each of the right eye E_(R) and theleft eye E_(L), the comparison value calculating unit 13 calculatesstatistics such as a mean value based on a plurality of feature amountstemporally continuously obtained during measurement as targets.

In addition, the result output unit 15 of the processor 9 outputsnumerical data, text data, or acquired images based on the comparisonvalue calculated by the comparison value calculating unit 13. Here, theresult output unit 15 may output data showing the comparison valueitself, or may output statistics of numerical data showing thecomparison value. In this case, the result output unit 15 calculatesstatistics such as a mean value based on a plurality of comparisonvalues temporally continuously obtained during measurement as targets.

Next, detailed steps of a comparison value measurement operation by thebinocular measurement system 1 will be described, and a binocularmeasurement method according to the present embodiment will be describedin detail. FIG. 3 and FIG. 4 are flowcharts showing steps of acomparison value measurement operation by the binocular measurementsystem 1. FIG. 3 shows steps in a case where statistics are calculatedbased on, as a target, a comparison value of eyeblink feature amounts bysimultaneously acquiring images of the right eye E_(R) and the left eyeE_(L), and FIG. 4 shows steps in a case where images of the right eyeE_(R) and the left eye E_(L) are acquired separately, an eyeblinkfeature amount and a statistic thereof are calculated for each of theright eye E_(R) and the left eye E_(L) separately, and a comparisonvalue of the two statistics is calculated. Either one of the functionsonly needs to be implemented in the binocular measurement system 1.

First, referring to FIG. 3, when a measurement operation is started,image signals of the right eye E_(R) and the left eye E_(L) aretemporally continuously and simultaneously acquired by the photodetector7 (Step S01). Next, by the feature amount calculating unit 11, temporalchanges of the upper eyelid positions of the right eye E_(R) and theleft eye E_(L) of the subject are calculated based on the image signals(Step S02). Then, by the feature amount calculating unit 11, based onthe temporal changes of the upper eyelid positions of the right eyeE_(R) and the left eye E_(L), eyeblink feature amounts of the respectiveright eye E_(R) and left eye E_(L) are temporally continuouslycalculated (Step S03). Thereafter, by the comparison value calculatingunit 13, a comparison value of the eyeblink feature amounts of therespective right eye E_(R) and left eye E_(L) is temporally continuouslycalculated (Step S04). Next, by the result output unit 15, statistics ofthe comparison value temporally continuously obtained are calculated(Step S05). Then, aggregated values of these statistics are calculatedand output (Step S06). In these Steps S05 and S06, aggregated values ofthe comparison value may be directly output without calculation ofstatistics of the comparison value.

Referring to FIG. 4, when a measurement operation is started, imagesignals of the right eye E_(R) and the left eye E_(L) are temporallycontinuously and separately acquired by the photodetector 7 (Steps S11and S12). Next, by the feature amount calculating unit 11, temporalchanges of the upper eyelid positions of the right eye E_(R) and theleft eye E_(L) of the subject are separately calculated based on theimage signals (Step S13). Then, by the feature amount calculating unit11, based on the temporal changes of the upper eyelid positions of theright eye E_(R) and the left eye E_(L), eyeblink feature amounts of theright eye E_(R) and the left eye E_(L) are temporally continuouslycalculated (Step S14). Thereafter, by the comparison value calculatingunit 13, statistics of the eyeblink feature amounts of the respectiveright eye E_(R) and left eye E_(L) are separately calculated (Step S15).Next, by the comparison value calculating unit 13, comparison values ofthe statistics of the right eye E_(R) and the left eye E_(L) arecalculated, and by the result output unit 15, these comparison valuesare output (Step S16). In these Steps S11 to S15, steps in which imagesignals of the right eye E_(R) and the left eye E_(L) are accumulatedand then the collective calculation is performed are adopted, however,it is also allowed that after image acquisition and calculationprocessing for the right eye E_(R) are performed, image acquisition andcalculation processing for the left eye E_(L) are performed.

According to the binocular measurement system 1 described above, basedon image signals of reflected light from the right eye E_(R) and theleft eye E_(L), an eyeblink feature amount related to the right eyeE_(R) and an eyeblink feature amount related to the left eye E_(L) arecalculated, and a comparison value is calculated by comparing the twoeyeblink feature amounts. Accordingly, an evaluation value related tobehavior of the eyes of the subject can be acquired by simplecalculation processing using a simple device configuration without aburden on the subject. Further, based on this evaluation value, behaviorof the eyes of the subject can be properly evaluated. In detail, brainfunctions can be non-invasively and easily quantified from behavior ofthe eyes.

Further, by using image signals obtained by an imaging device thatgenerates a two-dimensional image as a detection target, feature amountsof the right eye E_(R) and the left eye E_(L) can be accuratelyobtained, and as a result, eye behavior evaluation accuracy can beimproved.

Next, examples of measurement data obtained by the binocular measurementsystem 1 according to the present embodiment are shown.

A portion (a) of FIG. 5 shows frequency values of right-left differencesin time of maximum speed of eye closing in eye blinking of one subjectbefore and after performing a VDT work for 1 hour, and a portion (b) ofFIG. 5 shows frequency values of right-left differences of maximum speedof eye closing in eye blinking of one subject before and afterperforming a VDT work for 1 hour. Here, a right-left difference is avalue obtained by subtracting a value of the left eye from a value ofthe right eye, and a right-left difference being a positive value meansthat the value of the right eye is larger than the value of the lefteye. The results shown in the portion (a) of FIG. 5 show that aright-left difference in time of maximum speed of eye closing in eyeblinking becomes larger after the VDT work than before the VDT work, andthe left eye reaches the maximum speed earlier than the right eye afterthe VDT work. The results shown in the portion (b) of FIG. 5 also show asimilar tendency. That is, a right-left difference in maximum speed ofeye closing in eye blinking becomes larger after the VDT work thanbefore the VDT work, and the speed of the right eye was higher beforethe VDT work, and on the other hand, eye blinking in which the speed ofthe left eye is higher frequently occurs after the VDT work. In thebinocular measurement system 1, a healthy people database and a diseasedatabase are provided, and by calculating Mahalanobis' generalizeddistances between these databases and the measurement data, thedistances can be used as new feature amounts to quantify the functionsof the eyes when judging which of a healthy people group and a diseasegroup the measurement data is close to.

A portion (a) of FIG. 6 shows mean values of right-left differences intime of maximum speed of eye closing in eye blinking of three subjectsbefore and after a VDT work, and a portion (b) of FIG. 6 shows variancevalues of right-left differences in time of maximum speed of eye closingin eye blinking of three subjects before and after a VDT work. Theportion (a) of FIG. 6 shows that, after the VDT work, the right-leftdifference in time of maximum speed of eye closing in eye blinking tendsto increase after the VDT work in any of the three subjects. The portion(b) of FIG. 6 shows that variation in the right-left difference in timeof maximum speed of eye closing in eye blinking tends to increase afterthe VDT work in any of the three subjects.

A portion (a) of FIG. 7 shows standard deviations of right-leftdifferences in time of maximum speed of eye closing in eye blinking ofthree subjects before and after a VDT work, and a portion (b) of FIG. 7shows differences between maximum values and minimum values ofright-left differences in time of maximum speed of eye closing in eyeblinking of three subjects before and after a VDT work. The portion (a)of FIG. 7 shows that variation in the right-left difference in time ofmaximum speed of eye closing in eye blinking tends to increase after theVDT work in any of the three subjects. The portion (b) of FIG. 7 showsthat variation in the right-left difference in time of maximum speed ofeye closing in eye blinking tends to increase after the VDT work in anyof the three subjects.

A portion (a) of FIG. 8 shows maximum values of right-left differencesin time of maximum speed of eye closing in eye blinking of threesubjects before and after a VDT work, and a portion (b) of FIG. 8 showsminimum values of right-left differences in time of maximum speed of eyeclosing in eye blinking of three subjects before and after a VDT work.The portion (a) of FIG. 8 shows that the right-left difference in timeof maximum speed of eye closing in eye blinking tends to increase afterthe VDT work in any of the three subjects. The portion (b) of FIG. 8shows that eye blinking in which the right-left difference in time ofmaximum speed of eye closing in eye blinking becomes shorter (theright-left difference becomes zero in some cases) occurs after the VDTwork in any of the three subjects.

A portion (a) of FIG. 9 shows mean values of right-left differences inmaximum speed of eye closing in eye blinking of three subjects beforeand after a VDT work, and a portion (b) of FIG. 9 shows variance valuesof right-left differences in maximum speed of eye closing in eyeblinking of three subjects before and after a VDT work. The portion (a)of FIG. 9 shows that, after the VDT work, the right-left difference inmaximum speed of eye closing in eye blinking tends to increase in any ofthe three subjects. The portion (b) of FIG. 9 shows that, after the VDTwork, variation in the right-left difference in maximum speed of eyeclosing in eye blinking tends to increase in any of the three subjects.

A portion (a) of FIG. 10 shows standard deviations of right-leftdifferences in maximum speed of eye closing in eye blinking of threesubjects before and after a VDT work, and a portion (b) of FIG. 10 showsdifferences between maximum values and minimum values of right-leftdifferences in maximum speed of eye closing in eye blinking of threesubjects before and after a VDT work. The portion (a) of FIG. 10 showsthat variation in the right-left difference in maximum speed of eyeclosing in eye blinking tends to increase after the VDT work in any ofthe three subjects. The portion (b) of FIG. 10 shows that variation inthe right-left difference in maximum speed of eye closing in eyeblinking tends to increase after the VDT work in any of the threesubjects.

A portion (a) of FIG. 11 shows maximum values of right-left differencesin maximum speed of eye closing in eye blinking of three subjects beforeand after a VDT work, and a portion (b) of FIG. 11 shows minimum valuesof right-left differences in maximum speed of eye closing in eyeblinking of three subjects before and after a VDT work. The portion (a)of FIG. 11 shows that, after the VDT work, the right-left difference inmaximum speed of eye closing in eye blinking tends to increase in any ofthe three subjects. The portion (b) of FIG. 11 shows that, after the VDTwork, the right-left difference in maximum speed of eye closing in eyeblinking tends to increase in any of the three subjects.

FIG. 12 show examples in which, targeting a plurality of subjectsincluding healthy people and cranial nerve disease patients, statisticsof eyeblink feature amounts are calculated for each of the right andleft eyes, and then comparison values of the statistics are calculated.A portion (a) of FIG. 12 shows a distribution of mean values of maximumspeeds of eye closing in eye blinking of the left eyes, a portion (b) ofFIG. 12 shows a distribution of mean values of maximum speeds of eyeclosing in eye blinking of the right eyes, and a portion (c) of FIG. 12shows a distribution of right-left differences in mean value of maximumspeed of eye closing in eye blinking. From these results, it is foundthat the right-left difference in mean value of maximum speed of eyeclosing in eye blinking of a cranial nerve disease patient tends to belarger as compared with a healthy person.

A portion (a) of FIG. 13 shows mean values and standard deviations ofright-left differences in time of maximum speed of eye closing in eyeblinking of three subjects before and after a VDT work, and a portion(b) of FIG. 13 shows mean values and standard deviations of right-leftdifferences in maximum speed of eye closing in eye blinking of threesubjects before and after a VDT work. In each graph, a mean value isshown by a circle, and a standard deviation is shown by a bar length. Asshown in the portion (a) of FIG. 13, it was found that the difference intime became larger and variation in the difference in time became largerafter the VDT work than before the VDT work in any of the threesubjects. Also, as shown in the portion (b) of FIG. 13, it was foundthat the speed difference became larger and the variation in the speeddifference became larger after the VDT work than before the VDT work inany of the three subjects.

FIG. 14 and FIG. 15 show examples of calculation of frequencies ofright-left differences in statistics of eyeblink feature amounts of aplurality of subjects including healthy people and cranial nerve diseasepatients as targets. A portion (a) of FIG. 14 shows right-leftdifferences in mean value of upper eyelid movement amounts at the timeof eye closing in eye blinking, a portion (b) of FIG. 14 showsright-left differences in mean value of period of eye closing in eyeblinking, a portion (c) of FIG. 14 shows right-left differences in meanvalue of eye closure period, a portion (a) of FIG. 15 shows upper eyelidmovement amounts at the time of eye opening in eye blinking, a portion(b) of FIG. 15 shows right-left differences in mean value of period ofeye opening in eye blinking, and a portion (c) of FIG. 15 showsright-left differences in mean value of maximum speed of eye opening ineye blinking. These detection results also show that a right-leftdifference of a cranial nerve disease patient tends to increase ascompared with a healthy person.

The present invention is not limited to the above-described embodiment.

Details to be detected of a subject by the binocular measurement system1 described above may be other kinds.

For example, the binocular measurement system 1 may detect involuntaryeye movement of a subject. A configuration of a binocular measurementsystem 1 according to a modification in this case will be described witha focus on differences from the above-described binocular measurementsystem 1.

[Configuration for Detection of Involuntary Eye Movement]

When an imaging device such as a video camera or a profile sensor isused as the photodetector 7, the binocular measurement system 1 measuresa cornea reflected light, a pupil diameter, or a pupil center of asubject. When a light sensor such as a photodetector or a profile sensoris used as the photodetector 7, scleral reflected light may be measured.When detecting cornea reflected light, the feature amount calculatingunit 11 of the processor 9 obtains an eyeball position by gravity centerarithmetic operation on a bright spot image. The photodetector 7 or theprocessor 9 may calibrate a difference in movement amount caused by adifference in curvature of the cornea of a subject before measurement,or may have a function to indicate predetermined bright spots andfacilitate saccade between bright spots, and reflect a correctioncoefficient for calibration of a movement amount. However, even duringsaccade detection, a subject always makes involuntary eye movement andthe eyeball position when gazing at a bright spot fluctuates, so that itis also preferable to perform control to make bright spots flash, andcontrol to continue calibration until a stable correction coefficient isobtained. For example, when a vision camera is used as the photodetector7, an eyeball position can be calculated in real time at a predeterminedframe rate while continuing acquisition of image signals of a subject,so that bright spot control and image signal acquisition may becontinued until a movement width caused by saccade falls within apredetermined variation width (statistic such as a standard deviation).When detecting scleral reflected light, the photodetector 7 or theprocessor 9 calibrates an output value of the photosensor and an eyeballmovement amount.

The feature amount calculating unit 11 of the processor 9 calculates atemporal change of an eyeball position based on an image signal outputfrom the photodetector 7. In addition, the feature amount calculatingunit 11 calculates a temporal change of an eyeball position movementspeed (eyeball movement speed) based on the temporal change of theeyeball position. A portion (a) of FIG. 16 shows a temporal change of aneyeball movement speed calculated by the feature amount calculating unit11, and a portion (b) of FIG. 16 shows a temporal change of an eyeballposition calculated by the feature amount calculating unit 11. Eachcircle shown in the portion (b) of FIG. 16 shows an eyeball position ineach frame, and is calculated at time intervals of, for example, 1millisecond. The feature amount calculating unit 11 obtains the eyeballmovement speed by calculating a square root of the sum of squares of ahorizontal speed and a vertical speed. The speed is obtained by firstderivation of the temporal change of the eyeball position. As shown inthe portion (a) of FIG. 16, a peak of the eyeball movement speed isobserved according to a flick of the subject, and before and after thepeak, slow movement of the eyeball position accompanying drift movementand tremor movement is detected, and as shown in the portion (b) of FIG.16, eyeball position changes according to these movements are detected.

Then, based on the calculated eyeball position temporal change andeyeball movement speed temporal change, the feature amount calculatingunit 11 calculates an involuntary eye movement feature amount being afeature amount related to involuntary eye movement for each of the righteye E_(R) and the left eye E_(L), separately. First, by comparing thetemporal change of the eyeball movement speed with a speed thresholdV_(th1) set in advance, the feature amount calculating unit 11identifies a period T5 in which the speed threshold V_(th1) is exceededas a flick period, and identifies the other period T6 as a period ofdrift movement and tremor movement. Further, the feature amountcalculating unit 11 calculates, as the involuntary eye movement featureamount, a “flick period,” a “flick maximum speed,” a “flick start time,”a “flick ending time,” a “time of flick maximum speed,” a “flickfrequency,” a “flick angle at maximum speed,” an “angle of flickperiod,” a “flick movement distance,” and a “flick width” and so on. The“flick period” is calculated as a length of an observed flick period T5,the “flick maximum speed” is calculated as a maximum value of an eyeballmovement speed in the flick period, the “time of flick maximum speed” iscalculated as a time the maximum value is observed, and the “flickfrequency” is calculated as flick occurrence frequency in apredetermined period. The “flick period” may be calculated as, forexample, by using a quartile point of the flick maximum speed, a periodtwice as long as a half-value width of the maximum speed, may be apredetermined period before and after a section in which the speedthreshold is exceeded, or may be extracted after influences of tremorand drift are reduced by applying a bypass filter to the speed waveform.As shown in a portion (a) of FIG. 17, the “flick width” is calculated asa distance between an eyeball position X1 at a flick start time and aneyeball position X2 at a flick ending time, as shown in a portion (b) ofFIG. 17, the “flick movement distance” is calculated as a value obtainedby summing distances between observation positions from the flick startposition X1 to the flick ending position X2, as shown in a portion (c)of FIG. 17, the “flick angle at maximum speed” is calculated as an angleθ1 of a vector connecting points before and after an eyeball position X3at a point of time a maximum speed is detected, and as shown in aportion (d) of FIG. 17, the “angle of flick period” is calculated as anangle θ2 of a vector connecting the eyeball positions X1 and X2.

Here, instead of, or in addition to the involuntary eye movement featureamount related to flick, the feature amount calculating unit 11 maycalculate an involuntary eye movement feature amount related to tremor.In order to calculate a feature amount related to tremor, the featureamount calculating unit 11 extracts frequency components of 50 Hz ormore from the temporal change of the eyeball position in a period exceptfor the flick period, and calculates a feature amount based on thefrequency components as targets. The feature amount calculating unit 11calculates, as an involuntary eye movement feature amount related totremor, a frequency feature amount and a feature amount related to anamplitude of shaking of tremor being microvibration, such as a “peakfrequency by frequency analysis,” a “frequency power sum of frequencyanalysis results,” and an “amplitude,” etc. The frequency analysis is“DFT (Discrete Fourier Transform),” “Wavelet analysis,” or the like, andDFT may be replaced by FFT (Fast Fourier Transform). The “peakfrequency” is a frequency showing a highest power value in a frequencyspectrum obtained through each frequency analysis, and the “frequencypower sum” is calculated as a sum of power values of the frequencyspectrum in an arbitrary frequency band, and the “amplitude” iscalculated as a sum of movement amounts of the eyeball positionaccording to tremor or a movement amount in a period until the movementdirection is reversed.

The feature amount calculating unit 11 may calculate an involuntary eyemovement feature amount related to drift instead of, or in addition tothe involuntary eye movement feature amount related to flick or tremor.When calculating feature amount related to drift, the feature amountcalculating unit 11 extracts frequency components of less than 50 Hzfrom the temporal change of the eyeball position in a period except forthe flick period, and calculates a feature amount based on the frequencycomponents as targets. The feature amount calculating unit 11calculates, as involuntary eye movement feature amounts related todrift, a “fractal dimension,” a “peak frequency,” a “frequency powersum,” and an “amplitude,” and so on. The “fractal dimension” is obtainedby calculating a fractal dimension based on the extracted frequencycomponents as targets, and the “peak frequency” is calculated as a peakfrequency of a spectrum calculated based on the extracted frequencycomponents, and the “amplitude” is calculated as a sum of movementamounts of the eyeball position according to drift.

FIG. 18 to FIG. 22 are flowcharts showing steps of an operation tomeasure a comparison value by the binocular measurement system 1. FIG.18 shows steps of simultaneously acquiring images of the right eye E_(R)and the left eye E_(L) and calculating statistics based on a comparisonvalue of involuntary eye movement feature amounts as a target, FIG. 22shows steps of acquiring images of the right eye E_(R) and the left eyeE₁ separately, calculating an involuntary eye movement feature amountand a statistic thereof for each of the right eye E_(R) and the left eyeE_(L), separately, and calculating a comparison value of the twostatistics, and FIG. 19 to FIG. 21 show detailed steps of analysis ofinvoluntary eye movement. Either one of the functions shown in FIG. 18and FIG. 22 only needs to be implemented in the binocular measurementsystem 1. The steps shown in FIG. 18 and FIG. 22 are the same as thesteps shown in FIG. 3 and FIG. 4 except that the processing target is aninvoluntary eye movement feature amount.

Referring to FIG. 19, when calculating a feature amount related to flickfor each of the right eye E_(R) and the left eye E_(L), first, thefeature amount calculating unit 11 of the processor 9 calculates atemporal change of the eyeball position (Step S31). Next, by using atemporal change of an eyeball movement speed, the feature amountcalculating unit 11 detects a flick section (Step S32). Then, thefeature amount calculating unit 11 calculates a feature amount relatedto flick by using the temporal change of the eyeball position and thetemporal change of the eyeball movement speed in the flick section (StepS33).

Referring to FIG. 20, when calculating a feature amount related totremor for each of the right eye E_(R) and the left eye E_(L), thefeature amount calculating unit 11 of the processor 9 first calculates atemporal change of an eyeball position (Step S41). Next, the featureamount calculating unit 11 detects a flick section by using a temporalchange of an eyeball movement speed, and extracts a signal of thetemporal change in a section other than the flick section (step S42).Thereafter, the feature amount calculating unit 11 extracts frequencycomponents of 50 Hz or more from the extracted signal (Step S43). Then,the feature amount calculating unit 11 calculates a feature amountrelated to tremor by using the extracted temporal change of the eyeballposition (Step S33).

Referring to FIG. 21, when calculating a feature amount related to driftfor each of the right eye E_(R) and the left eye E_(L), the featureamount calculating unit 11 of the processor 9 first calculates atemporal change of an eyeball position (Step S51). Next, the featureamount calculating unit 11 detects a flick section by using a temporalchange of an eyeball movement speed, and extracts a signal of thetemporal change in a section other than the flick section (Step S52).Thereafter, the feature amount calculating unit 11 extracts frequencycomponents of less than 50 Hz from the extracted signal (Step S43).Then, the feature amount calculating unit 11 calculates a feature amountrelated to drift by using the extracted temporal change of the eyeballposition (Step S33).

Also by the binocular measurement system 1 according to the modificationdescribed above, evaluation values related to behavior of the eyes of asubject can be acquired by simple calculation processing using a simpledevice configuration without a burden on the subject. Further, based onthe evaluation values, the behavior of the eyes of the subject can beproperly evaluated, and brain functions can be quantified non-invasivelyand easily from the behavior of the eyes.

Next, examples of measurement data obtained by the binocular measurementsystem 1 of the present modification are shown.

A portion (a) of FIG. 23 shows right-left differences in flick maximumspeed of one subject before and after a VDT work, a portion (b) of FIG.23 shows right-left differences in time of flick maximum speed of onesubject before and after a VDT work, and a portion (c) of FIG. 23 showsright-left differences in flick maximum speed of six subjects before andafter a VDT work. These results show that the right-left differencesbecome larger and the variation in the difference is larger after theVDT work than before the VDT work.

A portion (a) of FIG. 24 shows frequency values of right-leftdifferences in flick width before and after a VDT work, a portion (b) ofFIG. 24 shows frequency values of right-left differences in flickmovement distance before and after a VDT work, a portion (c) of FIG. 24shows frequency values of right-left differences in flick angle at themaximum speed before and after a VDT work, and a portion (d) of FIG. 24shows frequency values of right-left differences in angle of flickperiod before and after a VDT work. These results show that theright-left differences in feature amount are larger after the VDT work.

A portion (a) of FIG. 25 shows mean values and standard deviations ofright-left differences in horizontal movement frequency of tremor beforeand after a VDT work, and a portion (b) of FIG. 25 shows mean values andstandard deviations of right-left differences in vertical movementfrequency of tremor before and after a VDT work. As shown in the portion(a) of FIG. 25, it was found that the difference in horizontal movementfrequency became larger and variation in the difference became largerafter the VDT work than before the VDT work. As shown in the portion (b)of FIG. 25, it was found that the difference in vertical movementfrequency became smaller after the VDT work than before the VDT work,however, variation in the difference became larger after the VDT workthan before the VDT work.

The binocular measurement system 1 may detect the pupils of a subject. Aconfiguration of a binocular measurement system 1 of a modification inthis case will be described with a focus on differences from thebinocular measurement system 1 described above.

[Configuration for Pupil Detection]

A binocular measurement system 1 of the present modification measures apupil area or a pupil diameter or the like of a subject. That is, thefeature amount calculating unit 11 of the processor 9 calculates atemporal change of a pupil area or a pupil diameter based on an imagesignal output from the photodetector 7.

In detail, the feature amount calculating unit 11 sets a luminancethreshold for an image signal, and maintains a luminance value of apixel with low luminance as compared with the luminance threshold, andchanges a luminance value of a pixel with high luminance as comparedwith the luminance threshold to a predetermined value (for example, amaximum value “255”) not less than the luminance threshold. As athreshold setting method in this case, a method in which an image signalis divided into small regions, a sum of luminance values is calculatedin each region, and a threshold for division between a dark area groupand a bright area group is adaptively obtained, a method in which ahistogram of luminance values in all regions of an image signal isgenerated, the numbers of pixels are accumulated from the dark side, anda luminance value at which a predetermined number of pixels is satisfiedis set as a threshold, a method in which a lowest luminance value of aportion higher than an eyelid position or a luminance value obtained byadding a standard deviation to a mean luminance value is set as athreshold, or a method using a fixed value, can be adopted. In thiscase, the feature amount calculating unit 11 may perform binarization ofimage processing so as to leave a pupil area. Thereafter, the featureamount calculating unit 11 removes noise other than cornea reflectedlight and the pupil area by applying erosion and dilation being imageprocessing techniques a plurality of times to an image signal. A corneareflected light part may be scattered and magnified due to influencesfrom a tear volume on the eye surface and an intraocular lens, and inthis case, it may be impossible to remove noise only by erosion anddilation. Therefore, it is preferable that the feature amountcalculating unit 11 obtains the presence of a bright area in a dark areaby applying labelling, etc., of image processing after the erosion andthe dilation, and directly blacks out the bright area. Then, the featureamount calculating unit 11 counts the number of pixels with luminancevalues less than the threshold, and calculates this number as a pupilarea. Further, the feature amount calculating unit 11 obtains a straightline crossing the center of gravity coordinates of cornea reflectedlight in the bright area in the dark area, obtains a length ofintersection of the pixel group with luminance values less than thethreshold obtained after the noise removal through the erosion and thedilation described above, and the straight line, and calculates thislength as a pupil diameter. As another calculation method, it is alsopossible that a gravity center arithmetic operation is performed byusing luminance information of right and left boundaries of theintersection of the pixel group and the straight line, one-dimensionalcoordinates of the right and left boundaries are obtained, and adistance between them is regarded as a pupil diameter, and a method inwhich pupil diameters obtained by applying a plurality of thresholds areaveraged, may be performed.

Then, based on the calculated temporal change of the pupil diameter, thefeature amount calculating unit 11 calculates a pupil feature amountbeing a feature amount related to the pupil for each of the right eyeE_(R) and the left eye E_(L), separately. As the pupil feature amount,the feature amount calculating unit 11 calculates at least one of a“required time from a mydriasis peak time to a miosis peak time,” a“required time from a miosis peak time to a mydriasis peak time,” a“change rate from a pupil diameter and area at a mydriasis peak to apupil diameter and area at a miosis peak,” and a “change rate from apupil diameter and area at a miosis peak to a pupil diameter and area ata mydriasis peak.” A portion (a) of FIG. 26 shows an example of atemporal change of an pupil diameter calculated by the feature amountcalculating unit 11, and a portion (b) of FIG. 26 shows times ofmydriasis peaks and times of miosis peaks detected by the feature amountcalculating unit 11. Thus, by the feature amount calculating unit 11, atime corresponding to a minimum value of the temporal change of thepupil diameter is detected as a time of a miosis peak, and a timecorresponding to a maximum value of the temporal change of the pupildiameter is detected as a time of a mydriasis peak.

FIG. 27 and FIG. 28 are flowcharts showing steps of an operation tomeasure a comparison value by the binocular measurement system 1. FIG.27 shows steps of calculating statistics based on a comparison value ofpupil feature amounts as a target by simultaneously acquiring images ofthe right eye E_(R) and the left eye E_(L), and FIG. 28 shows steps ofacquiring images of the right eye E_(R) and the left eye E_(L),separately, calculating a pupil feature amount and a statistic for eachof the right eye E_(R) and the left eye E_(L), separately, andcalculating a comparison value of the two statistics. In the binocularmeasurement system 1, either one of the functions shown in FIG. 27 andFIG. 28 needs to be implemented. The steps shown in FIG. 27 and FIG. 28are the same as the steps shown in FIG. 3 and FIG. 4 except that theprocessing targets are pupil feature amounts.

Even by the binocular measurement system 1 according to the modificationdescribed above, evaluation values related to behavior of the eyes of asubject can be acquired by a simple device configuration and simplecalculation processing without a burden on the subject. Further, basedon the evaluation values, the behavior of the eyes of the subject can beproperly evaluated, and the brain functions can be non-invasively andeasily quantified from the behavior of the eyes.

In the binocular measurement system 1 according to the embodimentdescribed above, a difference or a ratio is calculated as a comparisonvalue, and in this case, a section that could not be measured due to eyeblinking or the like is preferably reflected in an aggregated value asan exception. In addition, when it is difficult to stably detect a pupildiameter, an area of a pupillary area or an area or a diameter resultantfrom ellipse approximation may be used.

As an application example of the binocular measurement system 1according to the embodiment described above, it is expected that thesystem is used for diagnosis of disease conditions and for judgment ofprogression of a disease and follow-up after a treatment, etc., athospitals. It is also expected that the system is used for health carefor an individual person to check his/her own health, and forphysiological experiments and visual experiments in laboratories.

Here, in the binocular measurement device described above, it ispreferable that the comparison value calculating unit calculates acomparison value based on a difference or a ratio between a firstfeature amount and a second feature amount. With this configuration,behavior of the eyes of a subject can be properly evaluated by simplecalculation.

Also, the feature amount calculating unit may calculate feature amountsrelated to eye blinking as the first feature amount and the secondfeature amount, may calculate feature amounts related to involuntary eyemovement as the first feature amount and the second feature amount, andmay calculate feature amounts related to the pupils as the first featureamount and the second feature amount. By obtaining evaluation valuesbased on these feature amounts, behavior of both eyes of a subject canbe properly evaluated.

Further, it is also preferable that the photodetector includes atwo-dimensional photodetector having a light receiving surface on whicha plurality of pixels are two-dimensionally arrayed. By including such atwo-dimensional photodetector, feature amounts of the right eye and theleft eye can be accurately obtained, and as a result, evaluationaccuracy of behavior of the eyes can be improved.

INDUSTRIAL APPLICABILITY

An aspect of the present invention is used for a binocular measurementdevice, a binocular measurement method, and a binocular measurementprogram, and is to easily and properly evaluate differences in behaviorof the eyes of subjects.

REFERENCE SIGNS LIST

1 . . . binocular measurement system, 3R, 3L . . . light source, 5 . . .lighting control device, 7 . . . photodetector, 9 . . . processor, 11 .. . feature amount calculating unit, 13 . . . comparison valuecalculating unit, 15 . . . result output unit, 17 . . . synchronouscontrol unit, E_(L) . . . left eye, E_(R) . . . right eye

The invention claimed is:
 1. A binocular measurement device comprising:a photodetector configured to detect light from a right eye and a lefteye of a target person, and output a detection signal; and a processorelectrically coupled to the photodetector and configured to input thedetection signal, wherein the processor is configured to: calculate afirst feature amount corresponding to the right eye and a second featureamount corresponding to the left eye based on the detection signal; andcalculate, based on feature amounts of the first feature amount and thesecond feature amount, a comparison value obtained by comparing thefirst feature amount and the second feature amount, wherein theprocessor calculates feature amounts related to eye blinking as thefirst feature amount and the second feature amount, and wherein theprocessor calculates the feature amounts related to eye blinking by (i)calculating a temporal change of an upper eyelid position and a temporalchange of an upper eyelid movement speed for each of the right eye andthe left eye, separately, and (ii) calculating the feature amountrelated to eye blinking for each of the right eye and the left eye,separately, based on the calculated temporal change of the upper eyelidposition and the calculated temporal change of the upper eyelid movementspeed.
 2. The binocular measurement device according to claim 1, whereinthe processor is configured to calculate a comparison value based on adifference or a ratio between the first feature amount and the secondfeature amount.
 3. The binocular measurement device according to claim1, wherein the processor is configured to calculate feature amountsrelated to the pupils as the first feature amount and the second featureamount.
 4. The binocular measurement device according to claim 1,wherein the photodetector includes a two-dimensional photodetectorhaving a light receiving surface on which a plurality of pixels aretwo-dimensionally arrayed.
 5. A binocular measurement device comprising:a photodetector configured to detect light from a right eye and a lefteye of a target person, and output a detection signal; and a processorelectrically coupled to the photodetector and configured to input thedetection signal, wherein the processor is configured to: calculate afirst feature amount corresponding to the right eye and a second featureamount corresponding to the left eye based on the detection signal; andcalculate, based on feature amounts of the first feature amount and thesecond feature amount, a comparison value obtained by comparing thefirst feature amount and the second feature amount, wherein theprocessor calculates feature amounts related to involuntary eye movementas the first feature amount and the second feature amount, and whereinthe processor calculates the feature amounts related to involuntary eyemovement by (i) calculating a temporal change of an eyeball positionmovement speed for each of the right eye and the left eye, separately,(ii) comparing the temporal change of the eyeball position movementspeed for each of the right eye and the left eye with a predeterminedthreshold, (iii) identifying, for each of the right eye and the lefteye, separately, a period in which the threshold is exceeded by thetemporal change of the eyeball position movement speed as a period of aflick, and a period in which the threshold is not exceeded by thetemporal change of the eyeball position movement speed as a period ofdrift movement and tremor movement, and (iv) calculating, for each ofthe right eye and the left eye, separately, one or more feature amountsof the flick, the drift movement, and the tremor movement, as thefeature amount related to involuntary eye movement.
 6. The binocularmeasurement device according to claim 5, wherein the processor isconfigured to calculate a comparison value based on a difference or aratio between the first feature amount and the second feature amount. 7.The binocular measurement device according to claim 5, wherein thephotodetector includes a two-dimensional photodetector having a lightreceiving surface on which a plurality of pixels are two-dimensionallyarrayed.